6.03 Intro to EECS by Med Tech
Spring 2019
Students will learn fundamental concepts in information extraction and representation using biomedical signals generated from electrocardiograms (ECGs), glucose detectors, and magnetic resonance imagers. Topics include physical characterization and modeling of systems in the time and frequency domains; analog and digital signals and noise; basic machine learning including decision trees, clustering, and classification; and introductory machine vision. 6 Engineering Design Points.
Instructors: Elfar Adalsteinsson, Collin M Stultz
TA: Katherine W Young
Lecture: MW2 (34-101)
Information:
Explores biomedical signals generated from electrocardiograms, glucose detectors or ultrasound images, and magnetic resonance images. Topics include physical characterization and modeling of systems in the time and frequency domains; analog and digital signals and noise; basic machine learning including decision trees, clustering, and classification; and introductory machine vision. Labs designed to strengthen background in signal processing and machine learning. Students design and run structured experiments, and develop and test procedures through further experimentation.
Prereq: Calculus II (GIR), Physics II (GIR) Units: 4-4-4
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